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Found 215 Articles for Data Analysis
![Priya Mishra](https://www.tutorialspoint.com/assets/profiles/661458/profile/60_2023165-1685510322.jpg)
891 Views
Pattern recognition is a dynamic field with diverse applications across various domains. It involves the development of algorithms and techniques to identify and analyze patterns within data. From image recognition tasks like object and face recognition to speech and handwriting recognition, pattern recognition plays a crucial role. It is also utilized in fields like bioinformatics, finance, and robotics. This article explores the wide-ranging applications of pattern recognition and highlights its significance in today's technologically advanced world. Applications of Pattern Recognition Pattern recognition is a versatile field that has had a profound impact across a wide range of industries and ... Read More
![Vineet Nanda](https://www.tutorialspoint.com/assets/profiles/314505/profile/60_152032-1615183042.jpg)
5K+ Views
Dispersion and skewness are two important measures of statistical analysis that are used to study the distribution of data. Dispersion measures how much the data is spread out around its central tendency, whereas skewness measures the symmetry of the data. In this essay, we will discuss the difference between dispersion and skewness, their significance, and how they can be calculated. What is Dispersion? In statistics, dispersion is a measure of how distributed the data is meaning it specifies how the values within a data set differ from one another in size. It is the range to which a statistical distribution ... Read More
![Devang Delvadiya](https://www.tutorialspoint.com/assets/profiles/570828/profile/60_2508000-1671165075.jpg)
387 Views
While attempting to understand an interdisciplinary field, for example, ML, the principal question is how much maths is vital and the degree of maths is expected to grasp these strategies. ML is about maths, which thus assists in calculating that with canning gain from data to make an exact forecast. The forecast could be as straightforward as grouping canines or felines from a given arrangement of pictures or what items to prescribe to a client in light of past buys. Thus, it is vital to understand the maths ideas driving any focal ML calculation appropriately. Along these lines, it assists ... Read More
![Devang Delvadiya](https://www.tutorialspoint.com/assets/profiles/570828/profile/60_2508000-1671165075.jpg)
166 Views
Machine learning is a rapidly expanding discipline requiring programming, data analysis, and mathematics proficiency. Many people believe that the Coding Blocks app is a great method to learn machine learning and other computer languages, but not everyone would agree. The recommended practices for coding ML applications are discussed here. Coursera Coursera is among the most well-known MOOCs since it hosts content from some of the world's top universities. It provides a variety of machine learning courses taught by industry professionals that may be taken online. Coursera provides students with free and paid classes, allowing them to study at their speed. ... Read More
![Devang Delvadiya](https://www.tutorialspoint.com/assets/profiles/570828/profile/60_2508000-1671165075.jpg)
195 Views
Machine learning is silent, continual progress. Machine Learning (ML) is a branch of AI that analyses data to make predictions, provide suggestions, and enhance performance over time. It does this by training neural networks, which are complicated mathematical structures, on massive datasets. This capability to increase precision and velocity in human decision-making and productivity has the potential to revolutionize the financial services sector and is already doing so. Machine learning has advanced to the point where a new term, "deep learning, " has been coined to describe it. In 1930, the first neural networks were presented, designed to mimic the ... Read More
![Mithlesh Upadhyay](https://www.tutorialspoint.com/assets/profiles/655330/profile/60_3996324-1684216489.jpg)
2K+ Views
Normalization is a process of organizing data in a database to reduce redundancy and improve data consistency. Primary keys are really important in organizing information in a database. They help to make sure that every row in a table has a unique identification so that nothing gets mixed up or lost. In this article, we will discuss different normal forms based on primary keys and their importance in ensuring data consistency. Introduction Let's discuss how we make sure that data in databases is organized properly. We use something called "functional dependencies" to help us do this. Each table in ... Read More
![Pranavnath](https://www.tutorialspoint.com/assets/profiles/629838/profile/60_1502721-1680003383.jpg)
2K+ Views
Whenever we share data and information, it is very important to make sure the data reaches its destination; it is not lost somewhere through its path during transmission. If the communication is secure, then the time consumed will also be less. But before proceeding we must know that data encapsulation and decapsulation help in working and processing the data transmission. It provides reliability and security to the data that is being transferred from the sender to the receiver so that no unwanted access can happen. It also helps in hiding the complex details of the transmission system so that no ... Read More
![Satish Kumar](https://www.tutorialspoint.com/assets/profiles/562858/profile/60_1148539-1669800354.jpeg)
217 Views
Google Cloud Platform (GCP) is a cloud computing platform that offers a wide range of services to help businesses run their operations in the cloud. With its flexible and scalable infrastructure, GCP has become one of the most popular cloud platforms in recent years. If you're looking to learn how to use GCP to its fullest potential, taking a course is an excellent way to get started. In this article, we'll take a look at some of the best GCP courses available in 2023. Introduction to Google Cloud Platform If you're new to GCP, the Introduction to Google Cloud Platform ... Read More
![Vineet Nanda](https://www.tutorialspoint.com/assets/profiles/314505/profile/60_152032-1615183042.jpg)
1K+ Views
In scientific research, errors can occur during the measurement of data that can affect the accuracy and reliability of the results. These errors can be classified into two categories: systematic error and random error. While both types of errors can affect the accuracy of research findings, they differ in terms of their nature, causes, and consequences. This essay aims to provide a detailed explanation of the difference between systematic error and random error. What is Systematic Error? Systematic errors are caused by flaws in the measurement process that consistently bias the results in a particular direction. These errors are often ... Read More
![Tamoghna Das](https://www.tutorialspoint.com/assets/profiles/641995/profile/60_877476-1681905345.jpg)
993 Views
In big data analysis, PySpark is a stack that combines the popular programming language Python with the open-source big data framework Apache Spark. PySpark provides an excellent interface for big data analysis, and one important component of this stack is Spark's DataFrame API. Here, we'll provide a technical guide for those who want to create PySpark DataFrames, including helpful tips and real-world examples. What are the key advantages of pyspark and which industries mostly use it? Pyspark is a Python API for Apache Spark, which is a distributed computing framework that provides fast, scalable, and fault-tolerant data processing. Some ... Read More